Clinical importance in Alzheimer's disease: effects of anchor agreement and disease severity.

OBJECTIVES: Methods of evaluating clinically meaningful decline are critical in research on Alzheimer's disease. A common method of quantifying clinically meaningful change is to calculate an anchor-based minimal clinically important difference (MCID) score. In this approach, individuals who report a meaningful change serve as the "anchors", and the mean level of change for this group serves as the MCID. In research on Alzheimer's disease, there are several possible anchors, including patients, knowledgeable observers (e.g., a family member), and clinicians. The goal of this study was to examine the extent to which agreement among anchors impacts MCID estimation and whether this relationship is moderated by cognitive severity status. METHODS: Analyses were completed on a longitudinal sample of 2247 adults, aged 50-103, from the Uniform Data Set. Outcome measures included the Montreal Cognitive Assessment, Clinical Dementia Rating-Sum of Boxes, and Functional Activities Questionnaire. RESULTS: For all of the outcomes, the MCID estimate was significantly higher when meaningful decline was endorsed by all of the anchors compared to when there was disagreement among the anchors. In addition, the MCID estimate was higher with increasing severity of cognitive impairment. Finally, cognitive severity status moderated the influence of agreement among anchors on MCID estimation; as disease severity increased, anchor agreement demonstrated less influence on the MCID. CONCLUSIONS: MCID estimates based on one anchor may underestimate meaningful change, and researchers should consider the viewpoints of multiple anchors in constructing MCIDs, particularly in the early stages of cognitive decline.

Network analysis of neuropsychiatric symptoms in Alzheimer's disease.

BACKGROUND: Neuropsychiatric symptoms due to Alzheimer's disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment. METHODS: The network relationships of behavioral symptoms were estimated from Neuropsychiatric Inventory Questionnaire (NPI-Q) data acquired from 12,494 older adults with MCI and AD during their initial visit. Network analysis provides insight into the relationships among sets of symptoms and allows calculation of the strengths of the relationships. Nodes represented individual NPI-Q symptoms and edges represented the pairwise dependency between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. RESULTS: The analysis showed patterns of connectivity among the symptoms of the NPI-Q. The network (M = .28) consisted of mostly positive edges. The strongest edges connected nodes within symptom domain. Disinhibition and agitation/aggression were the most central symptoms in the network. Depression/dysphoria was the most frequently endorsed symptom, but it was not central in the network. CONCLUSIONS: Neuropsychiatric symptoms in MCI and AD are highly comorbid and mutually reinforcing. The presence of disinhibition and agitation/aggression yielded a higher probability of additional neuropsychiatric symptoms. Interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Future work will compare neuropsychiatric symptom networks across dementia etiologies, informant relationships, and ethnic/racial groups, and will explore the utility of network analysis as a means of interrogating treatment effects.

Cognitive-motor dual-task interference in Alzheimer's disease, Parkinson's disease, and prodromal neurodegeneration: A scoping review.

BACKGROUND: Cognitive-motor interference (CMI) is a common deficit in Alzheimer's (AD) disease and Parkinson's disease (PD) and may have utility in identification of prodromal neurodegeneration. There is lack of consensus regarding measurement of CMI resulting from dual task paradigms. RESEARCH QUESTION: How are individuals with AD, PD, and prodromal neurodegeneration impacted by CMI as measured by dual-task (DT) performance? METHODS: A systematic literature search was performed in six datasets using the PRISMA guidelines. Studies were included if they had samples of participants with AD, PD, or prodromal neurodegeneration and reported at least one measure of cognitive-motor DT performance. RESULTS: 4741 articles were screened and 95 included as part of this scoping review. Articles were divided into three non-mutually exclusive groups based on diagnoses, with 26 articles in AD, 56 articles in PD, and 29 articles in prodromal neurodegeneration, and results presented accordingly. SIGNIFICANCE: Individuals with AD and PD are both impacted by CMI, though the impact is likely different for each disease. We found a robust body of evidence regarding the utility of measures of DT performance in the detection of subtle deficits in prodromal AD and some signals of utility in prodromal PD. There are several key methodological challenges related to DT paradigms for the measurement of CMI in neurodegeneration. Overall, DT paradigms show good potential as a clinical method to probe specific brain regions, networks, and function; however, task selection and effect measurement should be carefully considered.

Network Analysis of Neuropsychiatric Symptoms in Alzheimer's Disease.

Background: Neuropsychiatric symptoms due to Alzheimer's disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment. Methods: The network relationships of behavioral symptoms was estimated from Neuropsychiatric Inventory Questionnaire (NPI-Q) data acquired from 12,494 older adults with MCI and AD during their initial visit. Network analysis provides insight into the relationships among sets of symptoms and allows calculation of the strengths of the relationships. Nodes represented individual NPI-Q symptoms and edges represented the pairwise dependency between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. Results: The analysis showed patterns of connectivity among the symptoms of the NPI-Q. The network ( M =.28) consisted of mostly positive edges. The strongest edges connected nodes within symptom domain. Disinhibition and agitation/aggression were the most central symptoms in the network. Depression/dysphoria was the most frequently endorsed symptom, but it was not central in the network. Conclusions: Neuropsychiatric symptoms in MCI and AD are highly comorbid and mutually reinforcing. The presence of disinhibition and agitation/aggression yielded a higher probability of additional neuropsychiatric symptoms. Interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Future work will compare neuropsychiatric symptom networks across dementia etiologies, informant relationships, and ethnic/racial groups, and will explore the utility of network analysis as a means of interrogating treatment effects.

A boot camp translation of Alzheimer's disease in Hispanic/Latino communities.

Introduction: Hispanics/Latinos (H/Ls) are significantly underrepresented in Alzheimer's disease (AD) research participant samples. This exclusion limits our interpretation of research findings and understanding of the causes of brain health disparities. The Engaging Communities of Hispanics/Latinos for Aging Research (ECHAR) Network was created to engage, educate, and motivate H/Ls for participation in brain aging research by addressing several barriers to inclusion, including health literacy and AD-related communication. Methods: We used a novel community-engaged method-Boot Camp Translation (BCT)-to translate medical jargon into action-based, community-relevant messages. H/L community members (n = 39) were recruited from three cities to work with local research teams and co-develop culturally responsive AD-related messaging. BCT meetings leveraged various techniques to identify key messages, the target audience for the messages, and methods to disseminate these messages. Themes were constructed collaboratively between BCT facilitators and community members as the group iteratively refined the conceptual framework and language for the main messages, with the goal to make AD messaging accessible for H/L community members. Results: H/L community members showed significant improvements in subjective understanding (Cohen's d = 0.75; P < 0.001) and objective knowledge of Alzheimer's disease (Cohen's d = 0.79; P < 0.001) at BCT completion. H/L community members identified key messages that converged for all three cities. These were related to reducing stigma, emphasizing brain health and risk mitigation, and acknowledging the impact of AD on multi-generational families/households. Participants also recommended sharing these messages with H/Ls across the lifespan using multi-media avenues. Discussion: The collaborative efforts identified culturally responsive and community-relevant messaging that may help address health literacy barriers contributing to AD-related disparities in H/L communities. HIGHLIGHTS: Hispanics/Latinos are underrepresented in Alzheimer's disease and related dementias (ADRD) research despite increased risk.Limited ADRD health literacy may act as a recruitment barrier.Boot Camp Translation (BCT) is a process that targets health communication.We carried out BCT in three cities to co-develop ADRD messaging.Results highlight regional similarities and differences in ADRD communication.

Urbanicity and cognitive functioning in later life.

Introduction: Prior research has shown disparities in cognitive functioning across the rural-urban continuum. We examine individual- and contextual-level factors to understand how and why urbanicity shapes cognitive functioning across older adulthood. Methods: Using a nationally representative sample from 1996 to 2016 waves of the Health and Retirement Study (HRS) and growth curve models, we assess urban-suburban-exurban differences in older adult cognitive functioning. Results: Results demonstrate that older adult men and women living in exurban areas, and older adult men in suburban areas, have lower cognitive functioning scores compared to their urban peers. Educational attainment and marital status contribute to but do not fully explain these differences. There were no differences in the trajectory over age, suggesting that urbanicity disparities in cognition occur earlier in life, with average differences remaining the same across older adulthood. Discussion: Differences in cognitive functioning across urbanicity are likely due to factors accumulating prior to older adulthood.

Global rural health disparities in Alzheimer's disease and related dementias: State of the science.

INTRODUCTION: Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place-based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators. METHODS: An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: "What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?" In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings. RESULTS: A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions. DISCUSSION: A location dynamics model and ADRD-focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities. HIGHLIGHTS: Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities. Defining the unique rural barriers and facilitators to cognitive health yields insight. The strengths and resilience of rural residents can mitigate ADRD-related challenges. A novel "location dynamics" model guides assessment of rural-specific ADRD issues.

Cortical thickness is related to cognitive-motor automaticity and attention allocation in individuals with Alzheimer's disease: a regions of interest study.

Alzheimer's disease (AD) is characterized by a distinct pattern of cortical thinning and resultant changes in cognition and function. These result in prominent deficits in cognitive-motor automaticity. The relationship between AD-related cortical thinning and decreased automaticity is not well-understood. We aimed to investigate the relationship between cortical thickness regions-of-interest (ROI) and automaticity and attention allocation in AD using hypothesis-driven and exploratory approaches. We performed an ROI analysis of 46 patients with AD. Data regarding MR images, demographic characteristics, cognitive-motor dual task performance, and cognition were extracted from medical records. Cortical thickness was calculated from MR T1 images using FreeSurfer. Data from the dual task assessment was used to calculate the combined dual task effect (cDTE), a measure of cognitive-motor automaticity, and the modified attention allocation index (mAAI). Four hierarchical multiple linear regression models were conducted regressing cDTE and mAAI separately on (1) hypothesis-generated ROIs and (2) exploratory ROIs. For cDTE, cortical thicknesses explained 20.5% (p = 0.014) and 25.9% (p = 0.002) variability in automaticity in the hypothesized ROI and exploratory models, respectively. The dorsal lateral prefrontal cortex (DLPFC) (ß = - 0.479, p = 0.018) and superior parietal cortex (SPC) (ß = 0.467, p = 0.003), and were predictors of automaticity. For mAAI, cortical thicknesses explained 20.7% (p = 0.025) and 28.3% (p = 0.003) variability in attention allocation in the hypothesized ROI and exploratory models, respectively. Thinning of SPC and fusiform gyrus were associated with motor prioritization (ß = - 0.405, p = 0.013 and ß = - 0.632, p = 0.004, respectively), whereas thinning of the DLPFC was associated with cognitive prioritization (ß = 0.523, p = 0.022). Cortical thinning in AD was related to cognitive-motor automaticity and task prioritization, particularly in the DLPFC and SPC. This suggests that these regions may play a primary role in automaticity and attentional strategy during dual-tasking.

Changes in ImPACT Cognitive Subtest Networks Following Sport-Related Concussion.

OBJECTIVE: High school athletes are administered ImPACT at the start of the academic year or sport season and again after suspected concussion. Concussion management involves the comparison of baseline and post-injury cognitive scores with declines in scores providing evidence for concussive injury. A network framework may provide additional information about post-concussive cognitive changes and expand characterization of sport-related concussion (SRC) recovery. DESIGN: Retrospective cohort study. SETTING: High school. PARTICIPANTS: High school athletes (n = 1553) were administered ImPACT at baseline (T1), post-SRC (T2 = 72 h of injury), and prior to return to play (T3 = within two weeks post-injury). INDEPENDENT VARIABLES: ImPACT cognitive subtest scores. MAIN OUTCOME MEASURES: Cognitive networks were calculated and compared over three time points. Centrality indices were calculated to determine the relative importance of cognitive variables within networks. RESULTS: Network connectivity increased from T1 to T2 and remained hyperconnected at T3. There was evidence of network reorganization between T1 and T3. Processing speed was central within each network, and visual memory and impulsivity became more central over time. CONCLUSIONS: The results suggest potential evidence of cognitive network change over time. Centrality findings suggest research specific to visual memory and impulse control difficulties during the post-concussion recovery period is warranted. Network analysis may provide additional information about cognitive recovery following SRC and could potentially serve as an effective means of monitoring persisting cognitive symptoms after concussion.

The Rey Auditory Verbal Learning Test: Cross-validation of Mayo Normative Studies (MNS) demographically corrected norms with confidence interval estimates.

OBJECTIVE: The Mayo Normative Studies (MNS) represents a robust dataset that provides demographically corrected norms for the Rey Auditory Verbal Learning Test. We report MNS application to an independent cohort to evaluate whether MNS norms accurately adjust for age, sex, and education differences in subjects from a different geographic region of the country. As secondary goals, we examined item-level patterns, recognition benefit compared to delayed free recall, and derived Auditory Verbal Learning Test (AVLT) confidence intervals (CIs) to facilitate clinical performance characterization. METHOD: Participants from the Emory Healthy Brain Study (463 women, 200 men) who were administered the AVLT were analyzed to demonstrate expected demographic group differences. AVLT scores were transformed using MNS normative correction to characterize the success of MNS demographic adjustment. RESULTS: Expected demographic effects were observed across all primary raw AVLT scores. Depending on sample size, MNS normative adjustment either eliminated or minimized all observed statistically significant AVLT differences. Estimated CIs yielded broad CI ranges exceeding the standard deviation of each measure. The recognition performance benefit across age ranged from 2.7 words (SD = 2.3) in the 50-54-year-old group to 4.7 words (SD = 2.7) in the 70-75-year-old group. CONCLUSIONS: These findings demonstrate generalizability of MNS normative correction to an independent sample from a different geographic region, with demographic adjusted performance differences close to overall performance levels near the expected value of T = 50. A large recognition performance benefit is commonly observed in the normal aging process and by itself does not necessarily suggest a pathological retrieval deficit.

Latent structure of cognitive tests is invariant in men and women with schizophrenia.

Studies comparing the cognitive functioning of men and women with schizophrenia have produced conflicting results which could arise from sex-based differences in the latent structure of cognitive abilities. The current study used multigroup confirmatory factor analysis to examine invariance in latent structure of cognitive abilities to between men and women with schizophrenia. Confirmatory factor analysis of an initial neurocognitive assessment (men n = 612, women n = 201) and cross-validation using second assessment (men n = 549, women n = 198) demonstrated that a bifactor seven-factor model fit the data best for both men and women. Invariance analyses further indicated this model was invariant across men and women at both assessments. Group comparisons indicated women had significantly higher scores for Semantic Memory, Verbal Memory, and General Cognitive factors, whereas men exhibited better performance on the Vigilance factor. Results indicate that cognition in SZ is characterized by both a general cognitive factor and specific domains for both men and women. Invariance analysis provides evidence that cognitive differences between men and women do not result from sex-based differences in the latent structure of cognitive abilities. Current results also indicate small but statistically significant neurocognitive differences between men and women with schizophrenia.

Frontal Metabolites and Alzheimer's Disease Biomarkers in Healthy Older Women and Women Diagnosed with Mild Cognitive Impairment.

BACKGROUND: Women account for two thirds of the prevalence and incidence of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Evidence suggest that sex may differently influence the expression of proteins amyloid-beta (Aß1-42) and tau, for which early detection is crucial in prevention of the disease. OBJECTIVE: We investigated the effect of aging and cerebrospinal fluid (CSF) levels of Aß1-42 and tau on frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) in a cohort of cognitively normal older women and women with MCI. METHODS: 3T single-voxel MRS was performed on the medial frontal cortex, using Point Resolved Spectroscopy (PRESS) and Mescher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) in 120 women (age range 50-85). CSF samples of Aß1-42 and tau and scores of general cognition were also obtained. RESULTS: Levels of frontal gamma aminobutyric acid (GABA+) were predicted by age, independently of disease and CSF biomarkers. Importantly, levels of GABA+ were reduced in MCI patients. Additionally, we found that levels of N-acetylaspartate relative to myo-inositol (tNAA/mI) predicted cognition in MCI patients only and were not related to CSF biomarkers. CONCLUSION: This study is the first to demonstrate a strong association between frontal GABA+ levels and neurological aging in a sample consisting exclusively of healthy older women with various levels of CSF tau and Aß1-42 and women with MCI. Importantly, our results show no correlation between CSF biomarkers and MRS metabolites in this sample.

A Novel Way of Measuring Dual-Task Interference: The Reliability and Construct Validity of the Dual-Task Effect Battery in Neurodegenerative Disease.

BACKGROUND: Decreased automaticity is common among individuals with neurodegenerative disease and is often assessed using dual-task (DT) paradigms. However, the best methods for assessing performance changes related to DT demands remain inconclusive. OBJECTIVE: To investigate the reliability and validity of a novel battery of DT measures (DT Effect-Battery (DTE-B)) encompassing three domains: task-specific interference, task prioritization, and automaticity. METHODS: Data for this retrospective cross-sectional study included 125 participants with Parkinson's disease (PD), 127 participants with Alzheimer's disease (AD), and 84 healthy older adults. Reliability analyses were conducted using a subset of each population. DTE-B measures were calculated from single and DT performance on the Timed Up and Go test and a serial subtraction task. Construct validity was evaluated via associations within the DTE-B and with theoretically supported measures as well as known-groups validity analyses. RESULTS: Good to excellent reliability was found for DTE-B measures of task interference (motor and cognitive DT effects) (ICCs≥.658) and automaticity (combined DT effect (cDTE)) (ICCs≥.938). Evidence for convergent validity was found with associations within the hypothesized constructs. Known-groups validity analyses revealed differences in the DTE-B among the healthy group and PD and AD groups (ps≤.001), excepting task prioritization (ps≥.061). CONCLUSIONS: This study provides evidence to support the DTE-B as a reliable measure of multiple constructs pertinent to DT performance. The cDTE demonstrated evidence to support its validity as a measure of automaticity. Further investigation of the utility of the DTE-B in both PD and AD, as well as other populations, is warranted.

Relationships between frontal metabolites and Alzheimer's disease biomarkers in cognitively normal older adults.

Elevated expression of ß-amyloid (Aß1-42) and tau are considered risk-factors for Alzheimer's disease in healthy older adults. We investigated the effect of aging and cerebrospinal fluid levels of Aß1-42 and tau on 1) frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) and 2) cognition in cognitively normal older adults (n = 144; age range 50-85). Levels of frontal gamma aminobutyric acid (GABA+) and myo-inositol relative to creatine (mI/tCr) were predicted by age. Levels of GABA+ predicted cognitive performance better than mI/tCr. Additionally, we found that frontal levels of n-acetylaspartate relative to creatine (tNAA/tCr) were predicted by levels of t-tau. In cognitively normal older adults, levels of frontal GABA+ and mI/tCr are predicted by aging, with levels of GABA+ decreasing with age and the opposite for mI/tCr. These results suggest that age- and biomarker-related changes in brain metabolites are not only located in the posterior cortex as suggested by previous studies and further demonstrate that MRS is a viable tool in the study of aging and biomarkers associated with pathological aging and Alzheimer's disease.

Examination of the reliability and feasibility of two smartphone applications to assess executive functioning in racially diverse older adults.

Inclusion of Black participants in clinical research is a national priority. Mobile applications and remote data collection may increase study access for diverse populations. This study examined the reliability and feasibility of two mobile smartphone application-based cognitive measures in a diverse middle aged and older adult sample. Black (n = 44; Mage = 59.93) and non-Hispanic white (NHW; n = 50; Mage = 61.06) participants completed traditional paper-based neuropsychological testing and two app-based measures, Arrows and Number Match. Intraclass correlations demonstrated poor to moderate reliability (range: .417-.569) between performance on the app-based versions and performance on the traditional versions. Performance score differences by racial group were not statistically significant. Both Black and NHW participants rated the app-based measures as feasible and acceptable, though Black participants endorsed a stronger likelihood of future use. These findings add to the growing literature on remote cognitive testing .

Bifactor model of cognition in schizophrenia: Evidence for general and specific abilities.

BACKGROUND: Despite extensive study of cognition in schizophrenia, it remains unclear as to whether cognitive deficits and their latent structure are best characterized as reflecting a generalized deficit, specific deficits, or some combination of general and specific constructs. METHOD: To clarify latent structure of cognitive abilities, confirmatory factor analysis was used to examine the latent structure of cognitive data collected for the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) for Schizophrenia study. Baseline assessment data (n = 813) were randomly divided into calibration (n = 413) and cross-validation samples (n = 400). To examine whether generalized or specific deficit models provided better explanation of the data, we estimated first-order, hierarchical, and bifactor models. RESULTS: A bifactor model with seven specific factors and one general factor provided the best fit to the data for both the calibration and cross-validation samples. CONCLUSIONS: These findings lend support for a replicable bifactor model of cognition in schizophrenia, characterized by both a general cognitive factor and specific domains. This suggests that cognitive deficits in schizophrenia might be best understood by separate general and specific contributions.

Subjective Memory Complaints in White and African American Participants.

OBJECTIVE: Subjective memory complaints (SMCs) are associated with mild cognitive impairment and dementia but are understudied in African Americans (AAs). We compared SMC endorsement in white and AA participants and evaluated predictors of diagnostic progression. METHODS: Initial visit variables, including SMC and memory performance, were compared within a cognitively normal race-matched sample of white and AA participants (Ntotal = 912; 456each race) to assess the presence and predictors of SMC, the predictors of future diagnostic progression, and the change in memory performance over time. RESULTS: More white (32.9%) than AA (24.3%) participants reported SMC (P < .01, ϕ = -.10). Subjective memory complaint was predicted by memory performance (B = -0.03, standard error [SE] = 0.013, odds ratio [OR] = .968, P < .05) and race (B = -0.99, SE = 0.080, OR = .373, P < .001). Subjective memory complaints and memory performance were associated with progression, χ2 (3, n = 912) = 102.37, P < .001. African American race (-2.05 ± 0.24 SE) and SMC (-0.45 ± 0.21 SE) were associated with worse memory performance at baseline and over time, χ2(3) = 13.54, P < .01. CONCLUSIONS: In contrast to previous research, our study found that SMC is associated with diagnostic progression and objective memory declines in both white and AA participants.

Rationale and Design of the Emory Healthy Aging and Emory Healthy Brain Studies.

Understanding the relationships between health and aging is essential for delaying morbidity and maximizing independence in aging populations as life expectancies increase. Loss of cognitive function is a feared age-associated condition and growing public health concern. Alzheimer's disease (AD), the most common cause of dementia, has no curative therapies. Characterizing the relationships between risk factors, biomarkers, and AD progression is critical for the development of effective disease prediction, clinical intervention, and ultimately, disease prevention. The Emory Healthy Aging Study (EHAS) and the Emory Healthy Brain Study (EHBS), which is nested within EHAS, aim to further the understanding of healthy aging and the pathogenesis of age-related illnesses in well-characterized, community-based prospective cohorts and to identify biomarkers for the earliest manifestations of AD for the facilitation of preventative interventions. The EHAS is an innovative, longitudinal, web-based study enrolling English-speaking adults in the U.S. who agree to be contacted for future studies. Using validated instruments, the annual questionnaire enquires about demographics, socioeconomics, self-reported cognitive function, personal and family medical history, lifestyle, and psychosocial factors. Cognitive assessments are also obtained using an ambulatory device. Nested within EHAS, the EHBS is enrolling up to 2,500 EHAS participants, 50-75 years old, who do not have a diagnosis of AD, mild cognitive impairment, or any other memory disorder. EHBS in-person, biennial study visits, include neuropsychological testing, cardiovascular measures, retinal and brain imaging, biospecimen collection (blood, cerebrospinal fluid, gut microbiome), and other assessments. Since spring 2016, EHAS and EHBS have enrolled 12,500 and 863 participants with completed baseline assessments, respectively. Data and biospecimens from EHBS participants will support a broad range of AD biomarker discovery efforts, and follow-up of EHAS participants will enable assessment of self-reported cognitive trajectories and accumulation of incident cases of a variety of health conditions. The EHAS design supports the interval deployment of new study instruments and targeted sampling for ancillary studies. This project will increase our knowledge about healthy aging, improve our understanding of risk factors for cognitive impairment and dementias, support development of biomarkers, and facilitate studies of age-associated disorders including AD.

A 'Framingham-like' Algorithm for Predicting 4-Year Risk of Progression to Amnestic Mild Cognitive Impairment or Alzheimer's Disease Using Multidomain Information.

BACKGROUND: There are no agreed-upon variables for predicting progression from unimpaired cognition to amnestic mild cognitive impairment (aMCI), or from aMCI to Alzheimer's disease (AD). OBJECTIVE: Use ADNI data to develop a 'Framingham-like' prediction model for a 4-year period. METHODS: We developed models using the strongest baseline predictors from six domains (demographics, neuroimaging, CSF biomarkers, genetics, cognitive tests, and functional ability). We chose the best predictor from each domain, which was dichotomized into more versus less harmful. RESULTS: There were 224 unimpaired individuals and 424 aMCI subjects with baseline data on all predictors, of whom 37 (17% ) and 150 (35% ) converted to aMCI and AD, respectively, during 4 years of follow-up. For the unimpaired, CSF tau/Aß ratio, hippocampal volume, and a memory score predicted progression. For those aMCI at baseline, the same predictors plus APOE4 status and functional ability predicted progression. Demographics and family history were not important predictors for progression for either group. The fit statistic was good for the unimpaired-aMCI model (C-statistic 0.80) and very good for the aMCI-AD model (C-statistic 0.91). Among the unimpaired, those with no harmful risk factors had a 4-year predicted 2% risk of progression, while those with the most harmful risk factors had a predicted 35% risk. The aMCI subjects with no harmful risk factors had a predicted 1% risk of progression those with all six harmful risk factors had a predicted 90% risk. CONCLUSION: Our parsimonious model accurately predicted progression from unimpaired to aMCI with three variables, and from aMCI to AD with five variables.